1b.Approach (from AD-416)
Corn kernel varieties with varying levels of resistance to aflatoxin producing fungi will be collected and imaged using a tabletop hyperspectral scanning imaging system. Kernels will be spectrally analyzed to determine how much the UV, visible, and near infrared portions of the electromagnetic spectrum differ from one corn variety to another. Cultures of aflatoxin producing and non-producing fungi will also be imaged and the spectral fingerprints will be collected to produce a "spectral library" of the different strains of fungi. These data will be used to determine if hyperspectral imaging can then be used to differentiate and quantitate the varying fungal strains and/or their aflatoxin production both in pure fungal culture and in fungally infected kernels from corn varieties either resistant or susceptible to aflatoxin contamination. Techniques also will be investigated during ongoing experiments to determine the best imaging environment in which to accomplish hyperspectral analyses, such as type and direction of lighting. Once appropriate algorithms are developed, the system will be tested in various laboratory and field experiments to determine the efficacy of the system.

3.Progress Report

Based on the initial reflectance based imaging experiments, a fluorescence hyperspectral (using many individual wavelengths of light from visible light, as well as, ultraviolet to infrared) imaging system was developed and used to study fluorescence hyperspectral properties of healthy and aflatoxin- (a potent carcinogen) contaminated corn kernels. The contaminated corn kernels were prepared by inoculating corn ears with Aspergillus flavus spores in the field. After imaging, each corn kernel was examined for aflatoxin concentration using single kernel chemical analysis. The results indicate fluorescence hyperspectral imaging has the potential for detecting aflatoxin-contaminated corn. A Fluorescence Peak Shift (FPS) phenomenon was identified among groups of kernels with different aflatoxin contamination levels. The peak shifted toward longer wavelength, in the blue region, for the highly contaminated kernels and vice versa. Highly contaminated kernels also had a lower fluorescence peak magnitude compared with the less contaminated kernels. It was also found that a general negative correlation exists between measured aflatoxin and the fluorescence image bands in the blue and green spectral regions. Additionally, more studies were directed into differentiating the responses from corn kernels infected with aflatoxin-producing and non-aflatoxin-producing Aspergillus flavus. The internal parts of the infected corn kernels were also imaged with the hyperspectral imager and a Scanning Electron Microscope. These studies could provide deeper understanding of the biological processes involved during Aspergillus flavus infection of corn kernels. An aflatoxin detection algorithm (a defined set of mathematical parameters to achieve a result) is under development by using significant wavelengths identified in the analysis. The algorithm is used with the prototype fluorescence multi-spectral imaging system. The fluorescence multi-spectral imaging system will have the ability to tune to specific key wavelengths for aflatoxin detection and will be suitable for rapid detection and easy deployment. The system is currently being tested in scaled-up experiments where groups of corn kernels are examined simultaneously for the detection of aflatoxin. Each image includes 25 grams of corn, which is half the size of a standard sample for chemical analyses widely used in grain inspection stations. A 1 kg sample processing system is also in the final construction and testing phase. Success in these endeavors would bring us closer to our objective of providing a means of identifying/quantifying aflatoxin in corn using non-destructive hyperspectral imaging. Research progress was monitored through site visits, phone calls, and reports.